AndreaBozzo/ceres-open-data-index huggingface dataset:
Replication Data for: “Phosphorus sorption and availability in an andosol after a decade of organic or mineral fertilizer applications: importance of pH and organic carbon modifications in soil as compared to phosphorus accumulation"

[Lien vers la fiche source] Dataset of the paper entitled "Phosphorus sorption and availability in an andosol after a decade of organic or mineral fertilizer applications: importance of pH and organic carbon modifications in soil as compared to phosphorus accumulation". We conducted a 10-years-old field experiment on an andosol and compared fields that had been amended with mineral or organic (dairy slurry and manure compost) fertilizers against a non-fertilized control. Water and Olsen extractions and inorganic phosphorus sorption experiments were realized on soils sampled after 6 and 10 years of trial. We also realized an artificial and ex situ alkalization of the control soil to isolate the effect of pH on the sorption capacity of inorganic phosphorus.
Dépôt de Fibrodat, la base de données de stockage associée à la gestion informatisée de la Fibrothèque de fibres de coton du Cirad

[Lien vers la fiche source] Cette base de données est le lieu de stockage des informations relatives aux entrées physiques de coton dans la Fibrothèque, une collection physique du Cirad transférée au Muséum National d’Histoire Naturelle (MNHN) à Paris (contacter via colhelper.mnhn.fr). Les tables de cette base de données sont liées directement à des tables attachées de l’applicatif Microsoft Access 2019 (Fibrotec_PcJPG.accdb) qui facilite la saisie et le contrôle de contenu des champs d’informations de chaque entrée physique en fibres de coton. Les fonctions de cet applicatif sont détaillées dans un document déposé dans Cirad Agritrop sous la référence : Gourlot J.-P., Auzoux S. et Giner M., 2024, Fibrothèque du Laboratoire de Technologie Cotonnière (LTC) du Cirad, transmis au MUSÉUM NATIONAL D'HISTOIRE NATURELLE, Document pour le Dataverse, 8 p.
Base de données source pour : Revue des plantes et autres substances naturelles de la pharmacopée traditionnelle en Polynésie française

[Lien vers la fiche source] Ces dernières années, les recherches sur la médecine traditionnelle de Polynésie française, tant du point de vue botanique qu'ethnobotanique, se sont intensifiées. Cependant, malgré ces avancées, le nombre exact d'espèces de plantes médicinales utilisées n'a jamais été déterminé. Afin de combler ce manque, nous avons entrepris une étude bibliographique, basée sur 59 références dont 35 ont été sélectionnées selon des critères prédéfinis. En couvrant une période allant de 1858 à 2023, notre analyse a permis de recueillir des données détaillées sur les diverses substances utilisées dans les remèdes traditionnels, notamment leurs noms, leurs usages, les modes de préparation et leurs localisations géographiques. Nous avons ainsi dressé une liste comprenant 304 espèces de plantes médicinales et 41 substances naturelles non végétales, pour lesquelles nous avons documenté un total de 5727 citations d'usage pour 200 maladies/symptômes traités. Cette étude a fait l'objet d'un article scientifique intitulé "Revue des plantes et autres substances naturelles de la pharmacopée traditionnelle en Polynésie française" et publié dans la revue Ethnopharmacologia n°71. La base de données présentée ici a été construite et analysée dans le cadre de cette étude.
Simbi database: historical hydro-meteorological time series and catchment attributes in Haiti, 1905-2005

[Lien vers la fiche source] Haiti is highly exposed to hydro-climatic hazards. However, no database exists for the scientific community to characterize these hazards. To fill this gap, hydro-climatic data were compiled to create the first historical database in Haiti. This database, called Simbi, will contribute to a better knowledge of Haitian catchment hydrology. Simbi provides hydro-climatic records for 24 Haitian catchments, available both at the monthly and daily timestep over the 1920-1940 period. Both observed and simulated (using rainfall-runoff models) streamflow series are available for each catchment. Additionally, the Simbi database contains (i) 156 monthly rainfall series over the 1905-2005 period, (ii) 59 daily rainfall series over the 1920-1940 period, and, (iii) 37 daily rainfall series over the 1948-1966 period, and (iv) 70 daily streamflow series and (v) 23 monthly air temperature series over the period 1920-1940. Digitization of paper archives received support from Fonds pour la Recherche et le Développement de la BRH (Haiti)
Microplastic concentrations in surface water of Urban Lakes in Danang, Vietnam, 2021

[Lien vers la fiche source] Microplastic (300-5000µm) concentrations in surface water were investigated in Sen lake, Hoa Phu lake, Ham Nghi lake, Cong Vien lake, Bo De lake, Bau Trang lake, Bau Tram lake of Da Nang city, Central Viet Nam, in April 2021 (dry season) and in December 2021 (wet season). Microplastics in water were sampled using a stainless steel bucket and filtered through a plankton net with a mesh size of 80 μm. The samples were extracted in the laboratory using enzymatic digestion and H2O2 30%, density separated by NaCl, and were filtered on GF-A filter. Then microplastics were observed by a stereomicroscope and classified into groups of shape, color, and size. Microplastic concentration was expressed as the number of particles per m3 (item m-3) for water.
Dépôt dataverse des documents de la Démarche Qualité sous accréditation ISO 17025 du Laboratoire de Technologie Cotonnière (LTC) du Cirad (2004-2023)

[Lien vers la fiche source] Le dépôt comprend la compilation en un seul fichier PDF de 87 documents de la pyramide documentaire du LTC et de quelques feuilles de calcul associées. Il s’agit du manuel d’assurance qualité du Laboratoire de Technologie Cotonnière (LTC), de procédures, de modes opératoires, de modes opératoires et d’instruction d’utilisation d’équipements de mesure des caractéristiques technologiques des fibres de coton, et de documents types permettant le fonctionnement au quotidien du laboratoire. Un document explicatif de Agritrop est associé à ce dépôt sous la référence : GOURLOT Jean-Paul, GINER Michel, GUELFUCCI Fabienne, FORESTIER-CHIRON Nelly, GUIFFREY Pascale, POITEL Mireille, LASSUS Serge, VIALLE Michèle, LAPEYRE Marie-Elyse, BRUNISSEN Chantale, FRYDRYCH Richard, FRANCALANCI Philippe, PAYET Laura, GUILLEMAIN Hélène, DE CLOEDT Liliane, FRUTEAU DE LACLOS Anne-Laure, GAWRYSIAK Gérard, BACHELIER Bruno, NIEWEADOMSKI Jean-Charles, , 2024. Démarche Qualité sous accréditation ISO 17025 du Laboratoire de Technologie Cotonnière (LTC) du Cirad - Présentation des documents essentiels. Cirad-Agritrop, 5 p.
Référentiel des domaines, des champs disciplinaires et des spécialités scientifiques du Cirad

[Lien vers la fiche source] Le référentiel scientifique du Cirad est une classification institutionnelle élaborée en 2005 pour caractériser les domaines, les champs disciplinaires et les spécialités des personnels scientifiques du Cirad. Mis en œuvre dans le système d’information des ressources humaines (SIRH) institutionnel, il permet de dénombrer et de suivre l’évolution des effectifs des scientifiques du Cirad par domaines, champs disciplinaires et spécialités. Dans le secteur de l’information scientifique et technique (IST), les données des effectifs scientifiques du Cirad par domaines sont utilisées pour identifier la tranche tarifaire d’abonnement du Cirad à des ressources documentaires spécialisées. La classification disciplinaire du Cirad est également utilisée lors d'analyses de publications d’auteurs Cirad. En 2022, le référentiel a fait l'objet de travaux d'alignement avec des référentiels scientifiques externes : OCDE, ERC, Re3data, Dataverse, Clarivate.
DATA4C+ - A thesaurus to define land management practices in agriculture and forestry for soil carbon storage

[Lien vers la fiche source] DATA4C+ is a thesaurus classifying and defining land management practices in agriculture and forestry for soil carbon storage. DATA4C+ thesaurus is focussed on land management practices identified in the scientific literature as drivers of soil organic carbon (SOC) changes. DATA4C+ thesaurus aim was to fill the gap of lack of a comprehensive thesaurus for land management practices which directly or indirectly affect SOC dynamics.
Risque de ruissellement selon des pentes à 7% sur l'île de La Réunion

[Lien vers la fiche source] Estimation d'un risque de ruissellement vers les cours d'eau du Domaine Public Fluvial de l'île de La Réunion selon des pentes supérieures ou égales à 7%. Le calcul de risque de ruissellement est effectué de manière itérative, en partant des cours d'eau et en progressant le long des pentes jusqu'à une distance de 200m de part et d'autre de ces cours d'eau. Le calcul est effectué sur une grille de cellules de 5m de résolution spatiale. A chaque itération, on calcule la pente par rapport aux points voisins déjà explorés et si cette pente est supérieure ou égale à 7% on marque les cellules concernées. Si la pente est inférieure, la progression à partir de ces cellules ne va pas plus loin. Ce que l'on obtient est une estimation de ce risque de ruissellement qui n'est basée que sur les différences d'altitudes entre les points. Il n'est donc pas tenu compte de la couverture du sol, de sa capacité d'infiltration, de sa rugosité ou autres facteurs de surface pouvant affecter ce ruissellement. Ces calculs on été réalisés à l'aide d'un programme écrit en langage Ocelet.
A global database of land management, land-use change and climate change effects on soil organic carbon

[Lien vers la fiche source] This dataset comprises data from a systematic review done after a comprehensive literature search using Scopus, Web of Science, Ovid publisher and Google Scholar for peer-reviewed meta-analyses and systematic reviews up to early 2020 that reported on soil organic carbon. This global database compiles the results of 13,632 primary studies from 217 meta-analyses, and more than 100 000 paired comparisons. We report a total of 15,983 effect sizes, 6,541 of them related to SOC, and 9,442 of them related to other associated soil, plant or atmosphere parameters. Each effect-size is precisely described, including measures of heterogeneity, precise type of intervention and outcome associated to ease its interpretation. We also provide a precise assessment of the quality of the meta-analyses. Finally, we also document the geographic origin of the primary studies. Our database represents, to our knowledge the widest and most rigorous analysis of available data on the subject. This database can help understanding drivers of SOC sequestration, associated co-benefits and possible drawbacks, as well as guiding future global climate policies. It can provide robust guidance to ongoing debated and serve as a basis in international panels such as the Intergovernmental Panel on Climate Change (IPCC).
Code and data for: New formula and conversion factor to compute basic wood density of tree species using a global wood technology database.

[Lien vers la fiche source] This dataset includes the R script, data and results associated to the following scientific article: Vieilledent G., F. J. Fischer, J. Chave, D. Guibal, P. Langbour and J. Gérard. 2018. New formula and conversion factor to compute basic wood density of tree species using a global wood technology database. American Journal of Botany. 105(10): 1-9. [DOI: [10.1002/ajb2.1175]]. [bioRxiv: 274068] Cirad ([https://www.cirad.fr]) is the French agricultural research and international cooperation organization working for the sustainable development of tropical and Mediterranean regions. Since the 1950s, scientists at Cirad have compiled data on wood characteristics for hundreds of tree species around the world. Data have been compiled in a unique global wood technology database. Combining our research results with the data from the wood technology database, we were able to compute the basic wood density for each tree and derive the Cirad wood density database (CWDD). The CWDD is available as a comma-separated values file: Cirad-wood-density-database‧csv. It includes basic wood-density data Db (in g/cm3) for 4022 trees collected in 63 countries (mostly tropical) and representing 872 species. Basic wood-density has been computed from the wood-density at 12% moisture D12 (in g/cm3), the volumetric shrinkage coefficient R (in %/%), and the fibre saturation point S (in %) for 3832 trees. When R or S values were not available (for 190 trees), the basic wood-density was estimated from D12 using a conversion factor of 0.828: Db = 0.828 D12.
Alignement de classifications disciplinaires

[Lien vers la fiche source] Alignement de classifications disciplinaires dans le cadre du projet BRIDGE (Bridge Research through Interoperable Data Governance and Environments, 2019-2022), financé par l'Agence nationale de la recherche (ANR, France, projet ANR-19-DATA-0013) et porté par l'IRD, le Cirad et INRAe. Ce projet vise à définir des règles de gouvernance d'entrepôts de données de recherche institutionnels dans le respect des principes FAIR (facile à trouver, accessible, interopérable, réutilisable). L'un des objectifs du projet est de mettre en correspondance des classifications disciplinaires (institutionnelles, nationales, internationales) selon les standards du web pour faciliter leur utilisation par des entrepôts de données et par d'autres plateformes comme les archives ouvertes. Basés sur la méthode développée par CODATA (Committee on Data for Science and Technology) dans le cadre de son programme FAIR Vocabularies, les résultats des différentes étapes de FAIRisation de vocabulaires appliquées à sept classifications disciplinaires (Dataverse, Clarivate, OCDE, OST, Re3data, ERC, Cirad) sont présentés et des perspectives esquissées. Celles-ci concernent : i) A court terme, la publication sur un site internet dédié des vocabulaires alignés ; ii) A moyen terme, la soumission pour diffusion de ces vocabulaires à des plateformes nationales (LOTERRE, Linked open terminology resources) et/ou internationales (LOV, Linked Open Vocabularies) ; iii) A plus long terme, l'ajout de nouvelles classifications (ARWU, U_Multirank, Scopus…) ainsi que l'alignement de classifications disciplinaires et thématiques, institutionnelles, nationales et internationales.
Gendered pounded yam product profile in Nigeria (2)

[Lien vers la fiche source] The WP1 Gendered Food Product Profile for pounded yam in Nigeria reflects the [final step] of an interdisciplinary five-step methodology developed to identify demand for quality characteristics among diverse user groups along the food chain ([Forsythe et al., 2022]). This methodology includes: [step 1)] interdisciplinary state of knowledge of the product ; [step 2)] gendered food mapping, which includes participatory research with men and women in rural communities regarding their product preferences and priorities; [step 3)] participatory processing diagnosis and quality characteristics ; and [step 4)] consumer studies in rural and urban areas of the product using different RTB varieties.
Gendered pounded yam product profile in Nigeria (1)

[Lien vers la fiche source] The WP1 Gendered Food Product Profile for pounded yam in Nigeria reflects the [final step] of an interdisciplinary five-step methodology developed to identify demand for quality characteristics among diverse user groups along the food chain ([Forsythe et al., 2022]). This methodology includes: [step 1)] interdisciplinary state of knowledge of the product ; [step 2)] gendered food mapping, which includes participatory research with men and women in rural communities regarding their product preferences and priorities ; [step 3)] participatory processing diagnosis and quality characteristics ; and [step 4)] consumer studies in rural and urban areas of the product using different RTB varieties.
MIRS Database on cassava cell wall to predict cooking time at CIAT, Colombia

[Lien vers la fiche source] This database contains 111 MIR (mid-infrared) spectra of cassava flours acquired at 23/10/2020 in CIRAD (Montpellier), by using Nicolet IS50R Research FTIR spectrometer. The cassava roots used to produce the flour samples are harvested at CIAT (Colombia) from 2 fields : "parentales" and "sensorial" in November 2019-February 2020. Five harvests (trials): 19-63, 19-64 & 20-02 are from the field parentales in 11/2019, 12/2019 and 01/2020 (9, 10, 11 months after planting), respectively; and 20-03 & 20-11 from field sensorial in 01/2020 and 02/2020 (10 and 11 months after planting). This database contains also laboratory data measured on the same cassava roots samples, such as DM, water absorption at 10 minutes of cooking (WA10), water absorption at 20 minutes of cooking (WA20), water absorption at 30 minutes of cooking (WA30), water absorption at optimum cooking time, optimum cooking time (OCT), gradient, max force, distance at max force, area, linear distance, end force : max force.
NIRS Database on Dried Grounded Cassava Flour for Moisture, Ash, Fat, Protein, Sugar, Starch & Amylose Calibrations at IITA, Nigeria

[Lien vers la fiche source] The dataset contains spectral data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) for prediction of Moisture, Ash, Fat, Protein, Sugar, Starch & Amylose of dried ground cassava
NIRS Database on milled Gari for Water Absorption Capacity, Bulk Density, Dispersibility, Titratable Acidity Calibrations at IITA, Nigeria

[Lien vers la fiche source] The dataset contains spectra data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) used for prediction of Water Absorption Capacity, Bulk Density, Dispersibility, and Titratable Acidity of milled gari.
NIRS Database on cassava milled Gari at IITA, Nigeria

[Lien vers la fiche source] This database consists of spectra data collected on milled gari using the benchtop FOSS Near-Infrared Spectrometer (NIRS) with serial number 3013-0857. A total of 64 spectra data were collected in a duplicate scan of 32 gari samples. The Spectra data were collected in IITA, Nigeria, in the year 2020. Repeatability of the NIRS was also checked by taking ten replicate measurements of a milled gari sample, and the RMSE (root means square error) was computed. The spectra data were collected using the developed SOP by the RTBfoods project.
NIRS Database on cassava un-milled Gari at IITA, Nigeria

[Lien vers la fiche source] This database consists of spectra data collected on un-milled gari using the benchtop FOSS Near Infrared Spectrometer (NIRS) with serial number 3013-0857. A total of 36 spectra data were collected by the duplicate scan of 16 gari samples. The Spectra data were collected in IITA, Nigeria, in the year 2020. Repeatability of the NIRS was also checked by taking 10 replicate measurements of an un-milled gari sample, and the RMSE was computed. The spectra data were collected using the developed SOP by the RTBfoods project.
NIRS Database on unmilled Gari for Water Absorption Capacity, Bulk Density, Dispersibility, Titratable Acidity Calibrations at IITA, Nigeria

[Lien vers la fiche source] The dataset contains spectra data obtained using XDS Rapid Content Analyzer (FOSS XDS, solid module) used for prediction of Water Absorption Capacity, Bulk Density, Dispersibility, and Titratable Acidity of unmilled gari.
NIRS Database on fresh blended yellow cassava for DM, HCN, TCC, TBC & cooking time at CIAT, Colombia

[Lien vers la fiche source] The database contains biophysical data (DM, HCN, TCC, TBC, cooking time) and NIRS data of 1056 samples of biofortified (yellow) cassava harvested at CIAT over several years (2016-2019). NIRS data was recorded on fresh blended cassava roots, using a Foss 6500 instrument. The objective of the study is to investigate correlations between biophysical data and NIRS data, using different statistical approaches to identify the one(s) that works best. Deep learning algorithms will also be tested to assess their potential for more accurate NIRS calibrations.
NIRS Database on intact fresh cassava roots for DM at IITA, Nigeria

[Lien vers la fiche source] The database for intact cassava roots consists of 240 spectra data collected using the benchtop FOSS Near Infrared Spectrometer with serial number 3013-0857. The spectra comprise the proximal, middle, and axial part of the cassava roots, with each section's duplicate scan. The Spectra data were collected in IITA, Nigeria, in the year 2019/2020. Dry matter content of each section was also provided from wet laboratory analysis. Repeatability of the NIRS was also checked by taking ten replicate measurements of intact roots, and the RMSE was computed. The spectra data were collected using the developed SOP by the RTBfoods project.
NIRS Database on fresh blended cassava for DM, Water absorption, texture parameters & cooking time (OCT) at CIAT, Colombia

[Lien vers la fiche source] This is a database of quality traits of boiled cassava landraces, harvested at CIAT (Colombia) from two field trials: "Parentales/progenitors (36 genotypes)" and "Sensorial (28 genotypes)" in November 2019-February 2020. Five harvests were conducted: 19-63, 19-64 & 20-02 are from the field parentales in November 2019, December 2019 and January 2020 (9, 10, 11 months after planting), respectively; and 20-03 & 20-11 from field sensorial in January 2020 and February 2020 (10 and 11 months after planting). The dataset contains biophysical data (dry matter, water absorption, texture parameters, cooking time) and NIRS data of 160 samples. NIRS data was recorded on fresh blended cassava roots, using a Foss DS2500 instrument. The objective of the study is (1) to build a database of biophysical quality traits (DM, Water absorption, texture parameters & cooking time) and NIRS data collected on the same fresh roots samples; (2) Investigate correlations between biophysical data and NIRS data and develop predictive equations, in order to replace biophysical analyses with faster NIRS analyses.
NIRS Database on Fresh Yam tuber for Dry Matter & Starch Calibrations at NRCRI, Nigeria

[Lien vers la fiche source] The dataset contains spectra data of intact yam tuber from the On-farm Verification Trial, harvested in Igbariam and Abakiliki locations in Nigeria obtained using QualitySpec Trek: S-10016 used to predict starch and dry matter of fresh yam
NIRS Database on Dried Yam for DM, Protein, Starch, Sugar, Hardness, Cohesiveness, Adhesiveness, Springiness, Extensibility Calibrations at INRAe-CIRAD, Guadeloupe

[Lien vers la fiche source] The dataset contains 174 spectra from ground dried yam samples cultivated in CIRAD, Roujol, Year 2016-2017 obtained using FOSS 6500 for DM, Protein, Starch, Sugar, Hardness, Cohesiveness, Adhesiveness, Springiness, Extensibility Calibrations
NIRS Database on fresh blended yam for Dry Matter & Starch at IITA, Nigeria

[Lien vers la fiche source] Multilocation yam samples havested in 2020 (16 genotypes, 2 reps and 2 locations)= 64 samples. Fresh yam tubers were blended and spectra data was collected. Dry matter and starch analysis was conducted on the scanned samples.
NIRS Calibration for Sugars on cooked freeze dried sweepotato

[Lien vers la fiche source] This database refers to spectra of 60 cooked and freeze dried sweetpotatoe genotypes from MDP in Uganda 2019 analyzed using a FOSS XDS spectrometer. 3-4 fresh roots per genotype were boiled, mixed, freeze dried and then scanned. Calibration results for fructose, glucose, saccharose and maltose show mainly high performance showing that NIRS can be applied very good for these traits on dried samples.